Nisha Rathode (Editor)

Stephen Muggleton

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Covid-19
Doctoral advisor  Donald Michie
Fields  Machine learning
Name  Stephen Muggleton

Stephen Muggleton wwwdocicacukshmstephenmuggletonphotoin2
Born  6 December 1959 (age 56) (1959-12-06)
Institutions  Imperial College London University of Oxford Turing Institute University of York
Alma mater  University of Edinburgh
Thesis  Inductive acquisition of expert knowledge (1987)
Doctoral students  Stephen Moyle Jose Santos
Known for  Inductive logic programming Robot Scientist
Books  Inductive acquisition of expert knowledge

Notable awards  FREng FBCS FIET FAAAI
Education  University of Edinburgh

Stephen muggleton logic based and probabilistic symbolic learning 2nd essence summer school


Stephen H. Muggleton FBCS, FIET, FAAAI,FECCAI, FSB, FREng (born 6 December 1959, son of Louis Muggleton) is Professor of Machine Learning and Head of the Computational Bioinformatics Laboratory at Imperial College London.

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Education

Muggleton received his Bachelor of Science degree in Computer Science (1982) and Doctor of Philosophy in Artificial Intelligence (1986) supervised by Donald Michie at the University of Edinburgh.

Career

Following his PhD, Muggleton went on to work as a postdoctoral research associate at the Turing Institute in Glasgow (1987–1991) and later an EPSRC Advanced Research Fellow at Oxford University Computing Laboratory (OUCL) (1992–1997) where he founded the Machine Learning Group. In 1997 he moved to the University of York and in 2001 to Imperial College London.

Research

Muggleton's research interests are primarily in Artificial intelligence. From 1997–2001 he held the Chair of Machine Learning at the University of York and from 2001–2006 the EPSRC Chair of Computational Bioinformatics at Imperial College in London. Since 2013 he holds the Syngenta/Royal Academy of Engineering Research Chair as well as the post of Director of Modelling for the Imperial College Centre for Integrated Systems Biology. He is known for founding the field of Inductive logic programming. In this field he has made contributions to theory introducing predicate invention, inverse entailment and stochastic logic programs. He has also played a role in systems development where he was instrumental in the systems Duce, Cigol, Golem, Progol and Metagol and applications — especially biological prediction tasks.

He worked on a Robot Scientist together with Ross D. King that is capable of combining Inductive Logic Programming with active learning. His present work concentrates on the development of Meta-Interpretive Learning, a new form of Inductive Logic Programming which supports predicate invention and learning of recursive programs.

References

Stephen Muggleton Wikipedia


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